Results 171 to 180 of about 645,156 (309)

A two-stage SCUC model for distribution networks considering uncertainty and demand response. [PDF]

Heliyon, 2023
Wang F, Gan L, Zhang P.
europepmc   +1 more source

Hippo pathway at the crossroads of stemness and therapeutic resistance in breast cancer

Molecular Oncology, EarlyView.
Dysregulation of the Hippo pathway drives nuclear accumulation of YAP/TAZ, activating stemness‐related transcriptional programs that sustain breast cancer stemness and fuel therapeutic resistance across subtypes, underscoring Hippo signaling as a targetable vulnerability. Figure created and edited with BioRender.com.
Giulia Schiavoni, Antonella Palmese, Stefano Scalera, Laura Cipriani, Davide Mascolo, Patrizia Vici, Teresa Arcuri, Lorena Filomeno, Eriseld Krasniqi, Giovanni Blandino, Giulia Bon, Marcello Maugeri‐Saccà   +11 more
wiley   +1 more source

Impacts of domestic electric water heater parameters on demand response: a simulative analysis of physical and control parameter impacts

, 2016
This paper analyzes the impact of the high dimensional parameter space of domestic electric water heaters (DEWH) for demand response (DR). To quantify the consumer comfort a novel metric is introduced considering a stochastic distribution of different ...
Turau, Volker, Venzke, Marcus, Lübkert, Tobias   +2 more
core  

Optimized economic scheduling of demand response in integrated energy systems considering dynamic energy efficiency and dynamic carbon trading. [PDF]

Sci Rep
Mao H, Deng Q, Zhang Z, Yang X.
europepmc   +1 more source

Comprehensive energy efficiency optimization algorithm for steel load considering network reconstruction and demand response. [PDF]

Sci Rep, 2023
Zang Y, Wang S, Ge W, Li Y, Cui J.
europepmc   +1 more source

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

Molecular Oncology, EarlyView.
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova, Michele Montrone, Uday Rangaswamy, Francesco Diversi, Irene Schiavo, Denise Ferrarini, Roberta Di Florio, Irene Longo, Michele Coscia, Nicola Zamboni, Giorgia Demontis, Lisa Veghini, Vincenzo Corbo, Remo Sanges, Paul Heppenstall   +14 more
wiley   +1 more source

Demand Response for Imported and Domestic Poultry Meat Products to Food Safety Regulations in Japan: An Application of the Almost Ideal Demand System Model [PDF]

This study estimates the response of Japanese consumersf demand for poultry meat to the food safety regulations at the border using the almost ideal demand system (AIDS) with a particular focus on the maximum residue limits (MRL) on pesticides and ...
Tsunehiro Otsuki
core  

Lightweight machine learning framework using temporal features for electric vehicle demand response forecasting on edge devices. [PDF]

Sci Rep
Durrani AM, Asar AU, Aziz A, Khan W, Yousaf MZ, Anjam F, Farooq U, Abdullah M, Shabaz M.   +8 more
europepmc   +1 more source

Differential expression of cancer‐related genes supports prediction of poor response to first‐line treatments in T‐ALL pediatric patients with high minimal residual disease

Molecular Oncology, EarlyView.
In the present work, we have identified a transcriptional signature based on the differential expression of six genes (BCL2&MAST4, HSH2D&LAT2, METRN&PITPNM2) that would facilitate the early detection of T‐cell acute lymphoblastic leukemia (T‐ALL) patients prone to a poor treatment response and could be implemented at diagnosis, along with other risk ...
Antonio Lahera, Laura Vela‐Martín, Pablo Fernández‐Navarro, José Luis López‐Lorenzo, Javier Cornago, Pilar Llamas, Eduardo Pérez‐Gómez, José Luis Marín‐Rubio, Manuel Fresno, Javier Santos, José Fernández‐Piqueras, María Villa‐Morales   +11 more
wiley   +1 more source

AI-enhanced multi-timescale optimization strategy for virtual power plants: Advancing losad forecasting and dynamic demand response integration. [PDF]

PLoS One
Xu G, Yang G, Bao J, Feng H, Zhang F, Zheng H.   +5 more
europepmc   +1 more source